Method for estimating number of tags in slotted aloha-based RFID system

ABSTRACT

Provided is a method for estimating the number of tags in a slotted Aloha-based RFID system, which can estimate the number of tags through a new statistical average scheme using the number of slots, the measured number of empty slots, and the measured number of ID slots. The estimating method includes the steps of: a) setting the number (N) of slots, the measured number (c 0 ) of empty slots, and the measured number (c 1 ) of ID slots as parameters; and estimating the number (n) of the tags by substituting the set values into n=(N−1)/(c 0 /c 1 ).

FIELD OF THE INVENTION

The present invention relates to a method for estimating the number oftags in a slotted Aloha-based RFID system; and, more particularly, to amethod for estimating the number of tags in a slotted Aloha-based RFIDsystem, which can estimate the number of tags through a new statisticalaverage scheme using the number of slots, the measured number of emptyslots, and the measured number of ID slots.

DESCRIPTION OF RELATED ART

Radio Frequency IDentification (hereinafter, referred to as RFID) is awireless data collection technology that can identify, track and managea product, animal, or person, to which a tag is attached, by reading orwriting data from/to the tag having unique identification information byusing radio frequency. The RFID system includes a plurality ofelectronic tags or transponders (hereinafter, referred to as tags)attached to a product or animal having unique identificationinformation, and an RFID reader or interrogator for reading or writingthe information contained in the tags. The RFID systems are classifiedinto a mutual induction scheme and an electromagnetic scheme, dependingon communication schemes between the reader and the tag. Also, the RFIDsystems are classified into a passive RFID system and an active RFIDsystem, depending on whether the tag has its own power source. Inaddition, the RFID systems are classified into a long wave RFID system,a medium wave RFID system, a short wave RFID system, an ultra short waveRFID system, and a microwave RFID system, depending on use frequencies.According to these classifications, various standards have beenestablished and is now preparing.

Accordingly, the RFID technology is a ubiquitous IT based technologythat acquires, processes and uses information in real time using theRFID tag attached to the product, thereby realizing high livingstandard. The RFID technology is considered as a core technology thatcan expand the information society by distribution innovation andsynchronization of real product and product information using barcode.Thus, various researches on the RFID technology are conducted around theworld.

In such an RFID system, when the reader queries the tag attached to theproduct, the tag sends its own identifier in response to the query, thusachieving tag identification. At this point, when only one tag exists inan identification zone of the reader, the tag identification can besimply processed. On the other hand, when a plurality of tags exist,collision occurs because the respective tags respond to the reader atthe same time. Large-scaled RFID system environment such as distributionhas to identify a large quantity of products in real time. Therefore, ananti-collision algorithm is essentially required to efficiently identifya plurality of tags. The anti-collision algorithm can be classified intoa tree based decision algorithm and a slotted Aloha-based statisticalalgorithm.

In recent years, the UHF band is recognized as the most suitable band inthe distribution fields. To meet the strong demand of the RFID markets,the standardization for the use of the UHF band is in rapid progress,compared with other bands. “ISO/IEC 18000-6 type B” that has beenalready approved as the international standard in August 2004 and“EPCglobal UHF Gen2” that is preparing for adoption of “ISO/IEC 18000-6type C” also use the slotted Aloha-based anti-collision algorithm. Inaddition, “ISO/IEC 18000-7” for the band of 433 MHz and “EPC C1” for theband of 13.56 MHz use the slotted Aloha-based anti-collision algorithm.

A general Aloha scheme transfers data at every transmission request. Onthe contrary, in the slotted Aloha-based anti-collision algorithm, atransmission time is divided into several time slots, and the respectivetags select arbitrary slots and transfer data. In the RFID system, whenthe reader transmits information on the number of slots to the tagexisting in the zone, the respective tags generate random number andselect slots and then respond to the reader by loading information to betransmitted on the slots. At this point, the information on the numberof the slots is contained as parameter in the query command. The IDslots having only one information can be identified by the reader.However, the slots having a plurality of information, that is, the slotswhere collision occurs cannot be identified, and the tags that loadinformation on these slots have to retransmit information at next roundor frame. Also, among the slots responding to the reader, the emptyslots where any information is not loaded are included. For theefficient tag identification, the number of slots is set such that aratio occupied by system efficiency, that is, the ID slots of all slotsbecomes highest. If the number of the slots is excessively large, itresults in waste of the slots. If the number of the slots is excessivelysmall, the collision rate between the tags increases. Thus, the numberof tags and the set number of slots in the zone determine the systemefficiency.

However, unlike the existing wireless communication, the RFID system hasa problem that cannot know the number of tags in the zone. Therefore,the estimation of the number of tags in the zone has to take precedence.Also, based on the estimated number of tags, the number of slots has tobe set to obtain the highest system efficiency.

SUMMARY OF THE INVENTION

It is, therefore, an object of the present invention to provide a methodfor estimating the number of tags in a slotted Aloha-based RFID system,which can estimate the number of tags through a new statistical averagescheme using the number of slots, the measured number of empty slots,and the measured number of ID slots.

In accordance with an aspect of the present invention, there is provideda method for estimating number of tags in a slotted Aloha-based RFIDsystem, the method comprising the steps of: a) setting the number (N) ofslots, the measured number (c₀) of empty slots, and the measured number(c₁) of ID slots as parameters; and b) estimating the number (n) of thetags by substituting the set values into n=(N−1)/(c₀/c₁).

BRIEF DESCRIPTION OF THE DRAWINGS

The above and other objects and features of the present invention willbecome apparent from the following description of the preferredembodiments given in conjunction with the accompanying drawings, inwhich:

FIG. 1 is a view of an RFID system in accordance with an embodiment ofthe present invention;

FIG. 2 is a flowchart illustrating a method for estimating the number oftags in a slotted Aloha-based RFID system in accordance with anembodiment of the present invention;

FIG. 3 is a graph illustrating comparison result of the prior art andthe present invention in the estimation of the number of tags;

FIG. 4 is a graph illustrating comparison of the set number of slotsthat can optimize the system efficiency based on the estimated number oftags in FIG. 3;

FIG. 5 is a graph of simulation result of the method for estimating thenumber of tags in the slotted Aloha-based RFID system in accordance withthe embodiment of the present invention; and

FIGS. 6A and 6B are graphs simulation results obtained by the method forestimating the number of tags in the slotted Aloha-based RFID system inaccordance with the embodiment of the present invention.

DETAILED DESCRIPTION OF THE INVENTION

Other objects and aspects of the invention will become apparent from thefollowing description of the embodiments with reference to theaccompanying drawings, which is set forth hereinafter.

FIG. 1 is a view of an RFID system in accordance with an embodiment ofthe present invention.

Referring to FIG. 1, the RFID system includes a tag 120 having unique IDinformation, and a reader 110 for recognizing the tag and reading the IDinformation from the recognized tag.

Hereinafter, a method for estimating the number of tags in a slottedAloha-based RFID system in accordance with the preferred embodiments ofthe present invention will be described in detail. The existing studieson the estimation of the number of tags within a predetermined regionwill be first described and a new statistical average method will bethen described. Moreover, the comparison and simulation results of thepresent invention and the prior art will be described.

Regarding the existing RFID system, standard and specification, such as“18000-6 type A”, “EPCglobal Gen 2”, “18000-7” and “EPC C1”, wasproposed. All of them use the slotted Aloha-based anti-collisionalgorithm, I-code algorithm, Bit-slot algorithm, and so on.

In order to explain a basic concept about the estimation of the numberof tags, a general algorithm will be first described.

A reader begins a tag identification process by querying a tag usingparameter of “p=<N, R, I>” where “N”, “R” and “I” represent the numberof slots, a seed value required for generating random values, and a tagidentifier range or an information on whether to participate in tagidentification, respectively. At this point, the selected tags withinthe region generate random values using the value of R. An arbitraryslot is selected within the range of the number of the slots, based onthe random value. Then, the tag identifier information of the selectedslot is loaded and transferred to the reader. The slot received by thereader may be the empty slot, the ID slot, or the collided slot.

States of the slots in one frame or one round are represented by “c=<c₀,c₁, c_(k)>”, where c₀, c₁ and c_(k) represent the number of empty slots,the number of ID slots, and the number of collided slots, respectively.Accordingly, the number of slots within a zone is estimated using thevalues c.

When “c₀” occupies most of the slots, the number of the slots mustdecrease. When “c_(k)” occupies most of the slots, the number of theslots must increase. If the number of the tags can be exactly estimated,the number of slots having the highest system efficiency must be newlyset, and next frame or next round is started.

Regarding the estimation of the number of tags, an error minimizationmethod is based on Cherbyshev's inequality. That is, all random valuesare generally distributed around an average expected value. Thus, theestimated value of the number of tags can be calculated using Eq. 1below.

$\begin{matrix}{{e_{vd}\left( {N,c_{0},c_{1},c_{k}} \right)} = {{\min\limits_{n}\begin{pmatrix}a_{0}^{N,n} \\a_{1}^{N,n} \\a_{k}^{N,n}\end{pmatrix}} - \begin{pmatrix}c_{0} \\c_{1} \\c_{k}\end{pmatrix}}} & {{Eq}.\mspace{14mu} 1}\end{matrix}$

In Eq. 1, “N”, “n”, “a₀ ^(N,n)”, “a₁ ^(N,n)”, and “a_(k) ^(N,n)”represent the number of slots, the number of tags, the average expectedvalue of c₀, the average expected value of c₁, and the average expectedvalue of c_(k). The number of tags is estimated as the value of “n” thatminimizes an error between the measured value and the expected value ofthe slot state.

However, the implementation of this error minimization method iscomplicated, and the error of the estimated value is determined by howmuch the measured value is close to the average expected value. Also,the error of the expected value is associated with the range of “n”.

Most of algorithms use a method of estimating a minimum value, which isimplemented more simply than the error minimization method. Theestimated value of the number of tags can be calculated using Eq. 2below.e _(min)(N,c ₀ ,c ₁ ,c _(k))=c ₁+2c _(k)  Eq. 2

The collided slots are generated because at least two tags are allocatedat the same time. Thus, the estimated number of the tags in Eq. 2 meansthe minimum value. The method of estimating the minimum value isadvantageous to estimate the number of the tags within two times rangeof the set number of the slots because a very large error occurs whenthe number of the tags exceeds two times the number of the slots, whichis set with the maximum value that can be estimated as shown in Eq. 3below.e _(min)(N,c ₀ ,c ₁ ,c _(k))=c ₁+2c _(k)=2N−2c ₀ −c ₁≦2N  Eq. 3

In the algorithm to which the above-described method is applied, thenumber of the tags is estimated through multi-steps. Also, the tags areefficiently identified by adjusting the number of the slots using afixed slot increase/decrease method, a proportional slotincrease/decrease method, or a log slot increase/decrease method, basedon the ratio that “c₀” or “c_(k)” occupies among the entire “c”.

FIG. 2 is a flowchart illustrating a method for estimating the number oftags in the slotted Aloha-based RFID system in accordance with anembodiment of the present invention.

Referring to FIG. 2, the number (N) of slots, the measured number (c₀)of empty slots, and the measured number (c₁) of ID slots are set in step201. The number (n) of tags is estimated by inserting the set value inton=(N−1)/(c₀/c₁) in step 202.

Hereinafter, the basic mathematic background about the slottedAloha-based anti-collision algorithm will be described.

When n number of tags communicates with the reader by using N number ofslots, a probability that r number of tags will exist within a singleslot follows a binomial distribution and can be expressed as Eq. 4below.

$\begin{matrix}{{B_{n.\;\frac{1}{N}}(r)} = {\begin{pmatrix}n \\r\end{pmatrix}\left( \frac{1}{N} \right)^{r}\left( {1 - \frac{1}{N}} \right)^{n - r}}} & {{Eq}.\mspace{14mu} 4}\end{matrix}$

Therefore, the average number of tags that can be read during one frameor round can be expressed as Eq. 5 below and the average number of emptyslots can be expressed as Eq. 6 below.

$\begin{matrix}{a_{1}^{N,n} = {{N \cdot {B_{n.\frac{1}{N}}(1)}} = {n\left( {1 - \frac{1}{N}} \right)}^{n - 1}}} & {{Eq}.\mspace{14mu} 5} \\{a_{0}^{N,n} = {{N \cdot {B_{n.\frac{1}{N}}(0)}} = {N\left( {1 - \frac{1}{N}} \right)}^{n}}} & {{Eq}.\mspace{14mu} 6}\end{matrix}$

If Eq. 6 is divided by Eq. 5, the result is given by Eq. 7 below.

$\begin{matrix}{{a_{0}^{N,n}/a_{1}^{N,n}} = {{{N\left( {1 - \frac{1}{N}} \right)}^{n}/{n\left( {1 - \frac{1}{N}} \right)}^{n - 1}} = {n\left( {N - 1} \right)}}} & {{Eq}.\mspace{14mu} 7}\end{matrix}$

Eq. 7 can be rewritten as follows.n=(N−1)/(a ₀ ^(N,n) /a ₁ ^(N,n))  Eq. 8

Therefore, the number of the tags is estimated by substituting themeasured values “c₀” and “c₁” into Eq. 8, instead of “a₀ ^(N,n)” and “a₁^(N,n)”. That is, the number of the tags is estimated using Eq. 9 below.n=(N−1)/(c ₀ /c ₁)  Eq. 9

As described in the error minimization method, the error of theestimated value in the proposed statistical average method is determinedby how much the measured value is closed to the average expected value.On the other hand, the statistical average method of the presentinvention has the simple calculation process and can be applied morewidely than the method of estimating the minimum value.

In order to verify the performance of the method for estimating thenumber of tags in the slotted Aloha-based RFID system in accordance withthe present invention, the comparison and simulation result between theprior art and the present invention will be described below.Specifically, the estimated number of tags, the optimal number of slotscalculated using the estimated number of the tags, the states of theslots whose number is four times and eight times the number of the tagswith respect to the set number of the slots, and the distribution of theestimated number of the tags will be compared and analyzed through thesimulation in comparison with the method of estimating the minimumvalue.

Parameters set for the simulation are as follows.

The number of tags is 16-256 and the number of slots is maximum 256. Forexample, the number of the slots may be 16, 32, 64, or 128.

FIG. 3 is a graph illustrating the comparison result of the prior artand the present invention in the estimation of the number of tags. InFIG. 3, a reference numeral 301 represents the estimated number (Npe) ofthe tags 301, which is estimated using the statistical average method ofthe present invention when the number of the slots is 64, a referencenumeral 303 represents the number (Nmin) of the tags, which is estimatedusing the method of estimating the minimum value, and a referencenumeral 302 represents the real number (Nr) of the tags with respect tothe increase in the number of the tags.

Referring to FIG. 3, although the error of the estimated value somewhatincreases according to the increase in the number of the tags, theestimating method of the present invention obtains the result close tothe real number of the tags, compared with the method of estimating theminimum value. Also, according to the method of estimating the minimumvalue, the error is very large when estimating more than 128 tags, whichcorrespond to two times the set number of the slots.

FIG. 4 is a graph illustrating the comparison of the set number of theslots that can optimize the system efficiency based on the estimatednumber of the tags in FIG. 3.

It can be seen from FIG. 4 that the estimated number (Npe) of the slotscalculated using the estimated number of the tags estimated by theestimating method of the present invention is very close to the number(opt) calculated using the real number of the tags. On the contrary, thenumber (Nmin) calculated using the number of the tags estimated by themethod of estimating the minimum value is set to be smaller than theoptimal number (opt) during the period where the number of the tags is64-84 and the period where the number of the tags is more than 142. Thismeans that the estimating method of the present invention improves thesystem efficiency much more than the method of estimating the minimumvalue.

FIG. 5 is a graph illustrating the simulation result of the method forestimating the number of tags in the slotted Aloha-based RFID system inaccordance with the embodiment of the present invention. Specifically,FIG. 5 illustrates the comparison of the number of the empty slots andthe number of the ID slots in one frame or round when the number of thetags is four times and eight times the number of the set number of theslots.

It can be seen from FIG. 5 that the average expected value of the emptyslot or the ID slot is not “1” when the number of the tags are eighttimes the number of the slots. That is, when the set number of the slotsis ⅛ time the number of the tags, “c₀” and “c₁” are “0”.

When the number of the tags is four times the number of the slots, “c₀”is not “1” until the number of the tags is 128, that is, the number ofthe slots is 32.). “c₀” is “1” when the number of the tags is 256, thatis, the number of the slots is 64. In this case, the number of the tagscannot be estimated using Eq. 9.

In the statistical average measuring method based on the slot's triplestate information “c=<c₀, c₁, c_(k)>”, when either or both of “c₀” and“c₁” becomes close to “0”, the error of the estimated value becomeslarge or the number of the tags cannot be estimated. On the contrary,when the number of the slots is very larger than the number of the tags,when the number (c_(k)) of the collided slots becomes close to “0”.However, because “c₀” or “c₁” contains much more information, theestimated number of the tags becomes more correct.

In order to merely estimate the number of the tags while ignoring thesystem efficiency, more correct result can be obtained by setting thenumber of the slots to be large. In estimating 16-256 tags, the proposedmethod can correctly estimate the number of the tags in almost allperiods when the initial number of the slots is set to 128.

The above results were based on the average expected values, and themeasured values have to be used in the real algorithm. Therefore, theerror of the estimated value is determined by how much the measuredvalue is close to the average expected value. Moreover, the systemefficiency is determined.

FIGS. 6A and 6B are graphs illustrating the simulation results obtainedby the method for estimating the number of tags in the slottedAloha-based RFID system in accordance with the present invention. Whenthe number of the tags is 128, the number of the slots is set to 64, 128and 256. At this point, the number of the tags estimated using themeasured values is illustrated in FIGS. 6A and 6B.

As illustrated in FIG. 6A, most of the measured values are distributedaround the average expected value of 128, but some of the measuredvalues have a very large error. In addition, when a large number of theslots are selected, the measured values are distributed much more aroundthe average expected value. Some of the measured values having largeerror can reduce the error with respect to the average expected valuevery easily by using the method of estimating the minimum value and thestates of the slots, as illustrated in FIG. 6B.

As described above, the method for estimating the number of tags in theslotted Aloha-based RFID system can improve the system efficiency byefficiently estimating the number of the tags through the anti-collisionalgorithm of the slotted Aloha-based RFID system.

The above-described methods in accordance with the present invention canbe stored in computer-readable recording media. The computer-readablerecording media may include CDROM, RAM, ROM, floppy disk, hard disk,optical magnetic disk, and so on. Since these procedures can be easilycarried out by those skilled in the art, a detailed description thereofwill be omitted.

The present application contains subject matter related to Korean patentapplication No. 2005-0105074, filed in the Korean Intellectual PropertyOffice on Nov. 3, 2005, the entire contents of which is incorporatedherein by reference.

While the present invention has been described with respect to certainpreferred embodiments, it will be apparent to those skilled in the artthat various changes and modifications may be made without departingfrom the scope of the invention as defined in the following claims.

1. A method for estimating the number of tags in a slotted Aloha-basedRFID system, the method comprising the steps of: a) setting the number(N) of slots, the measured number (c₀) of empty slots, and the measurednumber (c₁) of ID slots as parameters; and b) estimating the number (n)of the tags by substituting the set values into n=(N−1)/(c₀/c₁).
 2. Themethod as recited in claim 1, wherein the method for estimating thenumber of the tags is applied to an anti-collision algorithm of theslotted Aloha-based RFID system using a statistical average method.